Sentence examples for data subsections from inspiring English sources

The discussion in "Forum-type data" to "Search class data" subsections indicates that the main research direction for big data is the impact of investor sentiments on the financial sector (Antweiler and Frank 2004; Bartov et al. 2015; Sprenger et al. 2014a; Sabherwal et al. 2011).

Although there is some potential overlap between the source databases, in order to better focus the discussion, this section has been divided into ocean Bathymetric and Terrestrial specific data subsections.

The next subsection addresses quantitative assessment of the model and the data (Subsection 3.4).

We introduce the target conductivity model (Subsection 3.1), describe how we generate the test data (Subsection 3.2) and finally present the results of our model study (Subsection 3.3).

Without accounting for this effect, only the estimate of global C -responses from the observed data (Subsection 2.1) and the subsequent recovery of a conductivity model (Subsection 2.3) would be necessary.

In the Results we evaluate the cost criterion performances (subsection 1) and apply the indexes C, R and S to several kinds of simulated activities (subsection 2) and to real data (subsection 3) In subsections 2 and 3 we also compare the results obtained on simulations and on real data and the information provided by constant time bin and conditional sampling.

Details of this assessment can be found in ChiP-seq data subsection.

Details about the data, priors, evaluation methodology, and results can be found in the following ChiP-chip data subsection.

The LOE associated with the creation of such a consolidated dataset is discussed under the vector terrestrial elevation data subsection of the inventory.

This means that the beds in the department are occupied averaging around the occupation rate as indicated in the Collected data Subsection.

As the R-package QuACN was not introduced correctly in the Data subsection, we now introduce the package in the section Background.